An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems

Abstract

This paper is motivated by the growing penetration of renewable power plants in electrical systems worldwide and the scarcity of studies evaluating fault detection, classification, and localization tasks when applied within wind farms, i.e., their collector systems. In this context, the performance of existing fault detection and classification methods is assessed using single or multiple measurement points based on a measurement management approach presented in this work. For the studies, a system with a realistic topology of onshore wind farm collectors is modeled in the PSCAD software, and several fault scenarios varying fault type, resistance, inception angle, and location are represented, besides variations in the wind farm’s generation level. As the main contributions and novelties to the state-of-the-art, this paper provides: 1) pioneering insights about atypical faulty phase current behaviors in wind farm collector systems, 2) recommendations about conventional fault detection and classification methods that are most suitable for application in onshore wind farm collectors, and 3) an integrated methodology for fault detection, fault classification, and fault region identification in onshore wind farm collector systems.

Keywords

• Fault classification
• fault detection
• fault section identification
• inverter-based resources
• renewable generation
• wind farm collectors